Determinants vs. Algebraic Branching Programs
Abhranil Chatterjee, Mrinal Kumar, and Ben Lee Volk

TL;DR
This paper establishes a close relationship between determinantal complexity and algebraic branching program (ABP) complexity for homogeneous polynomials, showing that bounds on one imply bounds on the other, thus connecting two major open problems in algebraic complexity.
Contribution
It proves that for homogeneous polynomials, low determinantal complexity implies low ABP complexity, and for most polynomials, the ABP width is tightly bounded, linking two key complexity measures.
Findings
Homogeneous polynomials with determinantal complexity s can be computed by ABPs of size O(d^5 s)
For most homogeneous polynomials, the ABP width is just s-1 with size O(ds)
Super-linear lower bounds for ABPs imply similar bounds for determinantal complexity
Abstract
We show that for every homogeneous polynomial of degree , if it has determinantal complexity at most , then it can be computed by a homogeneous algebraic branching program (ABP) of size at most . Moreover, we show that for homogeneous polynomials, the width of the resulting homogeneous ABP is just and the size is at most . Thus, for constant degree homogeneous polynomials, their determinantal complexity and ABP complexity are within a constant factor of each other and hence, a super-linear lower bound for ABPs for any constant degree polynomial implies a super-linear lower bound on determinantal complexity; this relates two open problems of great interest in algebraic complexity. As of now, super-linear lower bounds for ABPs are known only for polynomials of growing degree, and for determinantal complexity the best lower bounds are larger…
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Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Advanced Combinatorial Mathematics · Advanced Graph Theory Research
